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At the architectural level, TPUs use a grid of multiply-accumulate (MAC) units—often referred to as a matrix multiply unit (MXU)—where data flows in a systolic (wave-like) pattern. Weights stream in from one side, activations from another, and intermediate results propagate across the grid without repeatedly accessing memory, drastically improving speed and energy efficiency. Execution is compiler-controlled rather than hardware-scheduled, enabling highly optimized and predictable performance. This design makes TPUs extremely powerful for large matrix operations central to AI.
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